Software Engineer, Tools and Automation

Responsibilities

• Define architecture and technical direction for internal tooling, workflow orchestration, integrations, data access, service boundaries, observability, and agentic systems where appropriate.
• Write production code for at least half of the time during the team’s first year and build the team’s testing, deployment, and production-support practices.
• Graduate departmental prototypes into production-grade systems and operate them under a you-build-it-you-run-it model.
• Design systems with multi-tenant isolation, secrets management, audit logging, encryption, role-based access controls, and human-in-the-loop controls.
• Develop templates, SDKs, sandboxes, and production patterns that enable departmental teams and internal AI builders.
• Partner with data, platform, infrastructure, security, and business teams to scope problems and deliver internal systems.
• Set standards for code quality, testing, evaluation, documentation, on-call practices, mentoring, and technical hiring.

Requirements

• 7+ years of professional software engineering experience building production systems with strong systems design and integration fundamentals.
• Demonstrated experience building and operating internal tools, automation, systems integrations, APIs, SaaS platform connections, or internal services used by colleagues.
• Production experience with at least two of Python, TypeScript/Node.js, and Go, with comfort working across the stack.
• Practical experience applying LLMs appropriately in workflows and evaluating when deterministic approaches are preferable.
• Experience building a platform, function, or product area from zero to one and scaling it.
• Experience in regulated or security-sensitive environments, including encryption, access controls, audit logging, and secrets management.
• Ability to provide technical leadership through influence, design reviews, mentoring, and independent decision-making.
• Strong communication skills with non-technical stakeholders and a product-first approach to shipping software.
• Interest in learning about life science; prior knowledge is not required.
• Preferred qualifications include enterprise SaaS, life sciences, or biotech experience; LLM orchestration and tool-integration familiarity; experience with Temporal, Prefect, or Airflow; familiarity with SOC 2, HIPAA, or GxP; internal developer-platform experience; coaching non-engineers on AI tooling; and model research or ML engineering experience.

Benefits

• Flexible hybrid work arrangement with in-office work prioritized three days per week: Monday, Tuesday, and Thursday.